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Sign up today to attend LIVE SESSIONS covering the latest overviews, insights, and how-to’s on today's central and evolving topics—AI, DC, DL, HPC, IoT, ML, oneAPI, and other essential acronyms—that you can use right away.

Miss a session? No problem. All past sessions can be accessed on-demand for your convenience. (All webinars are available 2 days after they air live.)

Wednesday, August 19, 2020 9:00 am PDT
#oneAPI

AI Analytics PART 2: Enhance Deep Learning Workloads on 3rd Gen Intel® Xeon® Scalable Processors

In the AI world, deep learning (DL) is foundational for any application’s ability to receive and analyze new information and correctly deduce its meaning. Part 2 of this 3-part series addresses DL workloads and how the AI Kit helps developers make it so.

Continuing the momentum from August 5th, this webinar (which is Part 2 in a 3-part series) looks at the Intel® AI Analytics Toolkit from the perspective of deep learning (DL) workloads.

As in … performance benefits and features that can enhance DL training, inference, and workflows.

Join software engineer Louis Tsai for this PART 2 session that delivers insights into the latest optimizations for Intel® Optimization for TensorFlow* and PyTorch which leverage the new acceleration instructions including Intel® DL Boost and BF16 support from 3rd Gen Intel® Xeon® Scalable processors.

Topics covered:

  • How to quantize a model from fp32/bf16 to int8 and analyze the performance speedup among different data types (fp32, bf16, and int8) in depth
  • Model Zoo for Intel® Architecture and low-precision tools included in the AI Kit
  • Efficiencies when building ML pipelines

Save your spot now.

Get the software
Download the Intel® AI Analytics Toolkit for Linux. Find out more. Download now.

Other resources

  • Read the latest Intel AI Analytics blogs on Medium.
  • Develop in the Cloud—Sign up for an Intel® DevCloud account, a free development sandbox with access to the latest Intel® hardware and oneAPI software.
  • Subscribe to the POD—Code Together is an interview series that explores the challenges at the forefront of cross-architecture development. Each bi-weekly episode features industry VIPs who are blazing new trails through today’s data-centric world. Listen and subscribe today.
Louie Tsai, Software Engineer, Intel Corporation

Louie is a Senior Software Engineer in Intel’s Technical Computing, Analyzers and Runtimes group. He is responsible for driving customer engagements with and adoption for Intel® Performance Libraries, leveraging the synergies between Python* and the Intel® Math Kernel Library (Intel® MKL). In addition, Louie focuses on embedded applications, with particular focus on autonomous driving and helping customers optimize their Deep Learning-related workloads. Louie has a Master’s degree in Computer Science and Information Engineering from National Chiao Tung University.

Wednesday, September 2, 2020 9:00 am PDT
#oneAPI

AI Analytics PART 3: Walk Through the Steps to Optimize End-to-End Machine Learning Workflows

In Part 3 of this 3-part series, you get the opportunity to watch and experience hands-on exercises using all the goodies—tools, features, and capabilities—found in the AI Kit.

Part 3 of this 3-part series shifts to “hands-on”, with presenters demonstrating the steps needed to execute key machine learning end-to-end workflows using the Intel® AI Analytics Toolkit.

Topics covered:

  • Highlighting optimizations in key workflow components running on Intel® architecture, including:
    • Intel’s integration of the OmniSciDB engine for Modin, a library that helps speed Pandas workflows by changing a single line of code.
    • XGBoost – An optimized, distributed, gradient-boosting library that implements ML algorithms under the Gradient Boosting framework.
    • Intel’s optimized implementation of Scikit-Learn – A library of simple, efficient tools for predictive data analysis through the daal4py library.
  • Showing the AI Kit’s ease of use and comprehensive nature as an enterprise analytics solution.
  • Demonstrating how to quickly test performance with a pre-built and externally available Jupyter notebook.

Save your spot now.

Get the software
Download the Intel® AI Analytics Toolkit for Linux. Find out more. Download now.

Other resources

  • Read the latest Intel AI Analytics blogs on Medium.
  • Develop in the Cloud—Sign up for an Intel® DevCloud account, a free development sandbox with access to the latest Intel® hardware and oneAPI software.
  • Subscribe to the POD—Code Together is an interview series that explores the challenges at the forefront of cross-architecture development. Each bi-weekly episode features industry VIPs who are blazing new trails through today’s data-centric world. Listen and subscribe today.
Meghana Rao, oneAPI & AI Evangelist, Intel Corporation

Meghana is an experienced software developer who wears two distinct hats: a technical marketing engineer and an IA developer evangelist. In her current role, she works with developers in evangelizing Intel’s AI, IoT, and oneAPI products and solutions. She is a technical speaker and author who is passionate about tech advocacy through training on advanced topics on Intel Technology. Meghana joined Intel in 2008 and holds a Bachelor’s degree in Computer Science and Engineering from Bangalore University, and a Master’s degree in Engineering and Technology Management from Portland State University, Oregon.

Anant Sinha, Software Applications Engineer, Intel Corporation

Anant is a Software Application Engineer who works with developers, helping them optimize their deep learning and machine learning applications for Intel architectures. Prior to joining Intel in 2018, he spent nearly 10 years as a software product engineer and software developer for Esri, a global market leader in the GIS (geographical information system) framework. Anant holds a Bachelor’s degree in Computer Science from BITS Pilani, Masters of Engineering in Computer Science from Cornell University, and Masters of Science in Computer Science from University of California, Riverside.

Rachel Oberman, AI Technical Consulting Engineer, Intel Corporation

Rachel is an AI Technical Consulting Engineer who helps customers optimize their workflows with data analytics and machine learning algorithms from Intel. Prior to joining Intel in 2019, she focused on geospatial analysis and data science, and founded geoLab—an undergraduate research lab, serving as its Director. Rachel holds a Bachelor’s degree in Computer Science and Data Science from the College of William & Mary.

Wednesday, September 9, 2020 9:00 am PDT
#CodeModernization

Find CPU & GPU Performance Headroom using Roofline Analysis

Your programs are only as awesome as their ability to capitalize on the hardware power they’re deployed on. Join this webinar to learn how a free Intel analysis tool can uncover hardware-imposed performance ceilings and help you kick them to the curb.

Understanding how hardware-imposed performance ceilings impact your code can be a pain in the … ummm … can be challenging. Commonly, developers struggle to assess the optimization tradeoffs between memory bottlenecks and compute utilization for both CPU and/or GPU code.

Enter Intel® Advisor and its Roofline Analysis feature, a visual representation of application performance in relation to hardware limitations, including memory bandwidth and computational peaks.

Join Technical Consulting Engineer and HPC programming expert Cedric Andreolli for a session covering:

  • How to perform GPU headroom and GPU caches locality analysis using Advisor Roofline extensions for oneAPI and OpenMP
  • An introduction to a new memory-level Roofline feature that helps pinpoint which specific memory level (L1, L2, L3, or DRAM) is causing the bottleneck
  • A walkthrough of Intel Advisor’s improved user interface

Sign up now.

Get the software
Download Intel® Advisor to follow along. Standalone | As part the Intel® oneAPI Base Toolkit

More resources

Cedric Andreolli, Software Technical Consulting Engineer, Intel Corporation

Cedric is a Technical Consulting Engineer responsible for supporting Intel® Software Development Tools, with special focus on Intel® Compilers and Intel® Advisor, particularly in the realm of high-performance computing. In addition, he has extensive experience in Android* development with applications for augmented reality via both OpenGL* and Radiance* lighting simulation tool.

Cedric holds a Bachelor’s in Computer Science from University of Rennes 1 in France. In his spare time, he enjoys playing guitar in rock bands, skiing, and playing ice hockey and football.

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